The Application of Weighted Co-occurred Keywords Time Gram in Academic Research
Temporal Sequence Discovery

Shuqing Li, Nanjing University
Ying Sun, University of Buffalo

Monday, 1:30pm

Summary

The discovery and visualization of temporal sequence of personalized academic
research can enhance the ability for discovering the latent trend of usersí
interests. In this paper, we propose a definition of weighted co-occurred
keywords time gram and use it as a basic unit to analyze the temporal
information in existed keywords collection. We further propose a method to get
the temporal sequence and temporal network based on these time grams. An
application of the proposed method in discovering academic research temporal
sequence is discussed, which includes techniques for acquiring extended
keywords, assigning weight to each keyword and co-occurred weight to each
keyword pair. A visualization tool is designed for browsing the temporal
networks identified. Finally, we report an experiment in the area of library and
information studies. The experiment results show the effectiveness of the
proposal method in helping users analyzing and portraying the evolution pattern
and developing trend of corresponding academic research.